Skills and MCP tagged “embeddings”

rag-implementation Seth Hobson skill This skill helps build RAG systems with vector search and LLM answers grounded in external documents. Use it for document Q&A and knowledge assistants. Claude Code CX Codex Cursor 13,906installs embedding-strategies Seth Hobson skill This skill helps choose embedding models, tune chunking, and assess quality for semantic search and RAG projects. Claude Code CX Codex Cursor 11,391installs similarity-search-patterns Seth Hobson skill This skill helps build similarity search with vector databases for semantic search, RAG retrieval, nearest-neighbor queries, and hybrid search. Claude Code CX Codex Cursor 10,700installs rag-architect Alireza Rezvani skill Design a RAG pipeline around your documents, then measure retrieval quality. Use it to explore chunking strategies, embeddings, or vector databases. Claude Code 629installs qdrant-search-quality official github skill Diagnoses why Qdrant returns irrelevant matches and points to ways to improve search quality. Useful after an embedding model change or as your data grows. GitHub Copilot 61installs qdrant-model-migration official github skill This skill guides Qdrant embedding-model migrations without taking search offline. Use it when changing providers, vector dimensions, or moving from dense to hybrid search. GitHub Copilot 61installs